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Record W2794899125 · doi:10.47756/aihc.y1i1.10

Towards development of an effective low-cost interactive whiteboard for promoting student engagement in sociology courses

2016· article· en· W2794899125 on OpenAlexafffund
Miguel Á. García-Ruiz, Vivian Jiménez Estrada, Deborah Woodman

Bibliographic record

VenueAvances en Interacción Humano-Computadora · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Technology Integration
Canadian institutionsAlgoma University
FundersAlgoma University
KeywordsInteractive whiteboardClass (philosophy)Context (archaeology)USableComputer scienceMathematics educationUsabilityStudent engagementWhiteboardActive learning (machine learning)MultimediaPsychologyHuman–computer interaction

Abstract

fetched live from OpenAlex

Interactive whiteboards (IWBs) can be a great asset to teachers trying to help students visualize what they are trying to teach, especially for supporting instructors and teams of students in class. However, commercial IWBs can be costly and difficult to operate. This paper describes the development of a low-cost IWB using a video game controller and “homebrew” infrared pens, and how its usability and technology acceptance will be tested in the context of sociology courses. We propose that the use of low-cost and highly-usable technologies in sociology courses may enhance student learning outcomes and retention rates as a way to fit the learning needs of students and supporting them in the engagement of critical thinking.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.526
Threshold uncertainty score0.672

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.026
GPT teacher head0.402
Teacher spread0.376 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2016
Admission routes2
Has abstractyes

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